🎬 video

video-analyzer

Video analysis tool, combining Llama visual model and OpenAI Whisper for local video description generation.

#natural language processing
#computer vision
#Video analysis
#audio transcription
#Run locally
#No API key required
video-analyzer

Product Details

video-analyzer is a video analysis tool that combines Llama's 11B visual model and OpenAI's Whisper model to describe what is happening in the video by extracting key frames, feeding them into the visual model to obtain details, and combining the details of each frame with the available transcripts. This tool represents a combination of computer vision, audio transcription, and natural language processing to generate detailed descriptions of video content. Its key benefits include running completely natively without a cloud service or API key, intelligent extraction of video keyframes, high-quality audio transcription using OpenAI’s Whisper, frame analysis using Ollama and Llama3.2 11B vision models, and generation of natural language descriptions of video content.

Main Features

1
Runs completely natively, no cloud services or API keys required
2
Increase speed and scale with openrouter’s LLM service
3
Intelligently extract keyframes from videos
4
High-quality audio transcription with OpenAI’s Whisper
5
Frame analysis using Ollama and Llama3.2 11B vision model
6
Generate natural language descriptions of video content
7
Automatically handle poor audio quality
8
Detailed JSON output analysis results
9
Highly configurable via command line parameters or configuration files

How to Use

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1. Clone the repository: git clone https://github.com/byjlw/video-analyzer.git
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2. Enter the project directory: cd video-analyzer
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3. Create and activate the virtual environment: python3.11 -m venv .venv
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4. Activate the virtual environment: source .venv/bin/activate (Windows users use .venv\Scripts\activate)
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5. Installation package: pip install . (regular installation) or pip install -e . (development installation)
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6. Install FFmpeg: Use the corresponding command to install FFmpeg according to the operating system
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7. Install Ollama and pull the default visual model: ollama pull llama3.2-vision
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8. Start the Ollama service: ollama serve
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9. Use video-analyzer to analyze video: video-analyzer path/to/video.mp4
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10. (Optional) If using OpenRouter, obtain the API key and configure it for use

Target Users

The target audience is video content analysts, video editors, researchers and anyone who needs to extract detailed information from videos. This tool is suitable for them because it provides an automated way to analyze video content, saving the time and effort of manual analysis, and can provide deeper insights than traditional methods.

Examples

Video content creators use video-analyzer to generate video summaries to improve the efficiency of content production.

Researchers use the tool to analyze video data and study behavioral patterns.

Educational institutions use video-analyzer to create detailed descriptions of instructional videos to assist visually impaired students in learning.

Quick Access

Visit Website →

Categories

🎬 video
› video editing
› AI information platform

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